Proceedings of SciPy 2010

SciPy 2010, the 9th annual Scientific Computing with Python conference, was held June 28 - July 3, 2010 in Austin, Texas. 18 peer reviewed articles were published in the conference proceedings.

Statsmodels: Econometric and Statistical Modeling with Python

Statsmodels is a library for statistical and econometric analysis in Python. This paper discusses the current relationship between statistics and Python and open source more generally, outlining how the statsmodels package fills a gap in this relationship.
Skipper Seabold, Josef Perktold
https://doi.org/10.25080/Majora-92bf1922-011

Audio-Visual Speech Recognition using SciPy

In audio-visual automatic speech recognition (AVASR) both acoustic and visual modalities of speech are used to identify what a person is saying. In this paper we propose a basic AVASR system implemented using SciPy, an open source Python library for scientific computing.
Helge Reikeras, Ben Herbst, Johan du Preez, +1
https://doi.org/10.25080/Majora-92bf1922-010

PySPH: A Python Framework for Smoothed Particle Hydrodynamics

PySPH is a Python-based open source parallel framework for Smoothed Particle Hydrodynamics (SPH) simulations. It is distributed under a BSD license. The performance critical parts are implemented in Cython.
Prabhu Ramachandran, Chandrashekhar Kaushik
https://doi.org/10.25080/Majora-92bf1922-00f

A Programmatic Interface for Particle Plasma Simulation in Python

Particle-in-Cell (PIC) simulations are a popular approach to plasma physics problems in a variety of applications. These simulations range from interactive to very large, and are well suited to parallel architectures, such as GPUs.
Min Ragan-Kelley, John Verboncoeur
https://doi.org/10.25080/Majora-92bf1922-00e

Numerical Pyromaniacs: The Use of Python in Fire Research

Python along with various numerical and scientific libraries was used to create tools that enable fire protection engineers to perform various calculations and tasks including educational instruction, experimental work, and data visualization.
Kristopher Overholt
https://doi.org/10.25080/Majora-92bf1922-00d

SpacePy - A Python-based Library of Tools for the Space Sciences

Space science deals with the bodies within the solar system and the interplanetary medium; the primary focus is on atmospheres and above—at Earth the short timescale variation in the the geomagnetic field, the Van Allen radiation belts and the deposition of energy into the upper atmosphere are key areas of investigation.
Steven K. Morley, Daniel T. Welling, Josef Koller, +3
https://doi.org/10.25080/Majora-92bf1922-00c

Protein Folding with Python on Supercomputers

Today's supercomputers have hundreds of thousands of compute cores and this number is likely to grow. Many of today's algorithms will have to be rethought to take advantage of such large systems. New algorithms must provide fine grained parallelism and excellent scalability.
Jan H. Meinke
https://doi.org/10.25080/Majora-92bf1922-00b

Data Structures for Statistical Computing in Python

In this paper we are concerned with the practical issues of working with data sets common to finance, statistics, and other related fields. pandas is a new library which aims to facilitate working with these data sets and to provide a set of fundamental building blocks for implementing statistical models.
Wes McKinney
https://doi.org/10.25080/Majora-92bf1922-00a

Modeling Sudoku Puzzles with Python

The popular Sudoku puzzles which appear daily in newspapers the world over have, lately, attracted the attention of mathematicians and computer scientists. There are many, difficult, unsolved problems about Sudoku puzzles and their generalizations which make them especially interesting to mathematicians.
Sean Davis, Matthew Henderson, Andrew Smith
https://doi.org/10.25080/Majora-92bf1922-009

Using Python with Smoke and JWST Mirrors

We will describe how the Space Telescope Science Institute is using Python in support of the next large space telescope, the James Webb Space Telescope (JWST). We will briefly describe the 6.5 meter segmented-mirror infra-red telescope, currently planned for a 2014 launch, and its science goals.
Warren J. Hack, Perry Greenfield, Babak Saif, +1
https://doi.org/10.25080/Majora-92bf1922-008

Rebuilding the Hubble Exposure Time Calculator

An Exposure Time Calculator (ETC) is an invaluable web tool for astronomers wishing to submit proposals to use the Hubble Space Telescope (HST). It provide a means of estimating how much telescope time will be needed to observe a specified source to the required accuracy.
Perry Greenfield, Ivo Busko, Rosa Diaz, +4
https://doi.org/10.25080/Majora-92bf1922-007

Weather Forecast Accuracy Analysis

ForecastWatch is a weather forecast verification and accuracy analysis system that collects over 70,000 weather forecasts per day. The system consists of data capture, verification, aggregation, audit and display components.
Eric Floehr
https://doi.org/10.25080/Majora-92bf1922-006

Unusual Relationships: Python and Weaver Birds

As colonial birds, weaver birds nest in groups in very particular trees and face specific challenges in the selection and establishment of their nests. Socially-living individuals may organize themselves in particular configurations to decrease the probability of events that could be detrimental to their own fitness.
Kadambari Devarajan, Maria A. Echeverry-Galvis, Rajmonda Sulo, +1
https://doi.org/10.25080/Majora-92bf1922-005

A High Performance Robot Vision Algorithm Implemented in Python

A crucial behavior for assistive robots that operate in unstructured domestic settings is the ability to efficiently reconstruct the 3D geometry of novel objects at run time using no a priori knowledge of the object.
Steven C. Colbert, Gregor Franz, Konrad Woellhaf, +2
https://doi.org/10.25080/Majora-92bf1922-004

Theano: A CPU and GPU Math Compiler in Python

Theano is a compiler for mathematical expressions in Python that combines the convenience of NumPy's syntax with the speed of optimized native machine language. The user composes mathematical expressions in a high-level description that mimics NumPy's syntax and semantics, while being statically typed and functional (as opposed to imperative).
James Bergstra, Olivier Breuleux, Frédéric Bastien, +6
https://doi.org/10.25080/Majora-92bf1922-003

Divisi: Learning from Semantic Networks and Sparse SVD

Singular value decomposition (SVD) is a powerful technique for finding similarities and patterns in large data sets. SVD has applications in text analysis, bioinformatics, and recommender systems, and in particular was used in many of the top entries to the Netflix Challenge.
Rob Speer, Kenneth Arnold, Catherine Havasi
https://doi.org/10.25080/Majora-92bf1922-002

Astrodata

The astrodata package is a part of the Gemini Telescope's python-based Data Reduction Suite. It is designed to help us deal in a normalized way with data from a variety of instruments and instrument-modes.
Craig Allen
https://doi.org/10.25080/Majora-92bf1922-001

Keeping the Chandra Satellite Cool with Python

The Chandra X-ray Observatory has been providing groundbreaking astronomical data since its launch by NASA in July of 1999. Now starting the second decade of science the Chandra operations team has been using Python to create predictive thermal models of key spacecraft components.
Tom Aldcroft
https://doi.org/10.25080/Majora-92bf1922-000